Global satellite navigation systems can provide users with all-weather, all-day, real-time, high-precision navigation and positioning services. However, there are many errors in satellite navigation and positioning, such as satellite clock error, satellite orbit error, ionospheric error, tropospheric error, and receiver clock error. The tropospheric error may cause a positioning error of up to 2 to 3 m.
The troposphere is the part of the Earth's atmosphere close to the ground, and contains approximately 75% of the atmosphere's mass and at least 90% of the total mass of water vapor. The thickness of the troposphere varies with the latitude. The atmosphere is thin at a high latitude and thick at a low latitude. Many atmospheric phenomena such as rain, snow, wind, and fog may occur in the troposphere. These weather phenomena can adversely affect the signal propagation.
When a satellite emits a signal downward, the signal is delayed due to the presence of substances such as water vapor in the atmosphere when passing through the troposphere. Such a delay is related to the atmospheric refractive index, and the atmospheric refractive index is related to the temperature and pressure in the atmosphere. The atmospheric refractive index may include dry atmospheric refractive index and wet atmospheric refractive index.
A ground-based augmentation system (GBAS) is a device that provides more accurate services for aircrafts during the approach and landing process. During the landing of an aircraft, the satellite navigation system cannot fully meet the aircraft's requirements on precision, integrity, and availability. Therefore, the GBAS is required to improve navigation precision, integrity and reliability. In the process of correction of the positioning error by the GBAS, the tropospheric error cannot be ignored. The tropospheric error is inseparable from the atmospheric refractive index.
However, because GBASs at different places are set up at different time points, the amounts of climatological data acquired by the GBASs are different, and the amounts of meteorological data of the GBASs are also different. Different meteorological data affect the prediction of atmospheric refractive index, leading to low precision in tropospheric refractive index prediction.
Therefore, in order to solve the problems in the prior art, there is a need for a ground-based augmentation system capable of predicting a tropospheric refractive index with high precision, to improve the precision of tropospheric refractive index prediction.